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During analysis, model selection may involve specification and comparison of multiple models.
— R Function A Day (@rfunctionaday) May 23, 2021
The {compare_performance} function from {performance} 📦 creates tabular + graphical summaries comparing performance indices for models 🥇https://t.co/6cAI5ZbNkl#rstats #DataScience pic.twitter.com/CxyfyRCCHY
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— NumFOCUS (@NumFOCUS) May 23, 2021
---
title: "#rstats Twitter Explorer"
output:
flexdashboard::flex_dashboard:
orientation: rows
vertical_layout: scroll
source_code: embed
theme:
version: 4
bootswatch: yeti
css: styles/main.css
---
```{r setup, include=FALSE}
library(flexdashboard)
library(rtweet)
library(dplyr)
library(httr)
library(lubridate)
library(echarts4r)
devtools::load_all()
rstats_tweets <- read_twitter_csv("data/rstats_tweets.csv")
count_timeseries <- rstats_tweets %>%
ts_data(by = "hours")
tweets_today <- rstats_tweets %>%
filter(created_at == today())
by_hour <- rstats_tweets %>%
group_by(hour = hour(created_at)) %>%
summarise(count = n()) %>%
ungroup()
number_of_unique_tweets <- get_unique_value(rstats_tweets, text)
number_of_unique_tweets_today <-
get_unique_value(tweets_today, text)
number_of_tweeters_today <- get_unique_value(tweets_today, user_id)
number_of_likes <- rstats_tweets %>%
pull(favorite_count) %>%
sum()
```
Home
====
Row
-----------------------------------------------------------------------
### Tweets Today
```{r}
valueBox(number_of_unique_tweets_today, icon = "fa-comment-alt", color = "plum")
```
### Tweeters Today
```{r}
valueBox(number_of_tweeters_today, icon = "fa-user", color = "peachpuff")
```
### #rstats Likes
```{r}
valueBox(number_of_likes, icon = "fa-heart", color = "palevioletred")
```
### #rstats Tweets
```{r}
valueBox(number_of_unique_tweets, icon = "fa-comments", color = "mediumorchid")
```
Row {.tabset .tabset-fade data-width=400}
-----------------------------------------------------------------------
### Tweet volume
```{r}
count_timeseries %>%
e_charts(time) %>%
e_line(n, name = "# of tweets", smooth = TRUE) %>%
e_x_axis(
type = "time",
formatter = htmlwidgets::JS(
"function(value){
let date = new Date(value);
label = `${date.getDate()}-${(parseInt(date.getMonth()) + 1)}-${date.getFullYear()}`;
return label;
}"
)
) %>%
e_axis_labels(y = "Tweets") %>%
e_theme("westeros") %>%
e_tooltip(trigger = "axis", formatter = htmlwidgets::JS("
function(params) {
let date = new Date(params[0].value[0])
let options = { year: 'numeric', month: 'short', day: 'numeric', hour: 'numeric'}
let title = `${date.toLocaleDateString('en-US', options=options)}`
let num = `${params[0].value[1]} tweets`
return(`${title}${num}`);
}"))
```
### Tweets by Hour of Day
```{r}
by_hour %>%
e_charts(hour) %>%
e_step(count, name = "Tweets", step = "middle") %>%
e_x_axis(
min = 0,
max = 23,
) %>%
e_axis_labels(x = "Time of Day (UTC)", y = "Tweets") %>%
e_theme("westeros") %>%
e_tooltip(trigger = "axis", formatter = htmlwidgets::JS("
function(params) {
let title = `${params[0].value[0]}h`
let num = `${params[0].value[1]} tweets`
return(`${title}${num}`);
}"))
```
Row
-----------------------------------------------------------------------
### 💗 Most Liked Tweet Today {.tweet-box}
```{r}
most_liked_url <- tweets_today %>%
slice_max(favorite_count)
get_tweet_embed(most_liked_url$screen_name, most_liked_url$status_id)
```
### ✨ Most Retweeted Tweet Today {.tweet-box}
```{r}
most_retweeted <- tweets_today %>%
slice_max(retweet_count)
get_tweet_embed(most_retweeted$screen_name, most_retweeted$status_id)
```
### 🎉 Most Recent {.tweet-box}
```{r}
most_recent <- tweets_today %>%
slice_max(created_at, with_ties=FALSE)
get_tweet_embed(most_recent$screen_name, most_recent$status_id)
```
Data
====
Locations
=========